Technology Report:

Computed Tomography (CT)

Contributing Editor Greg Freiherr offers an overview of computed tomography (CT) advances at the Radiological Society of North America (RSNA) 2015. The video includes Freiherr during his booth tours with some of the key vendors who were featuring new technology.

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Figure 1: Examples of chest CT images of COVID-19 (+) patients and visualization of features correlated to COVID-19 positivity. For each pair of images, the left image is a CT image showing the segmented lung used as input for the CNN (convolutional neural network algorithm) model trained on CT images only, and the right image shows the heatmap of pixels that the CNN model classified as having SARS-CoV-2 infection (red indicates higher probability). (a) A 51-year-old female with fever and history of exposure to SARS-CoV-2. The CNN model identified abnormal features in the right lower lobe (white color), whereas the two radiologists labeled this CT as negative. (b) A 52-year-old female who had a history of exposure to SARS-CoV-2 and presented with fever and productive cough. Bilateral peripheral ground-glass opacities (arrows) were labeled by the radiologists, and the CNN model predicted positivity based on features in matching areas. (c) A 72-year-old female with exposure history to the animal market in Wuhan presented with fever and productive cough. The segmented CT image shows ground-glass opacity in the anterior aspect of the right lung (arrow), whereas the CNN model labeled this CT as negative. (d) A 59-year-old female with cough and exposure history. The segmented CT image shows no evidence of pneumonia, and the CNN model also labeled this CT as negative.

Axial (A) and coronal (B) CT of the abdomen and pelvis with IV contrast in a 57-year-old man with a high clinical suspicion for bowel ischemia. There was generalized small bowel distension and segmental thickening (arrows), with adjacent mesenteric congestion (thin arrow in B), and a small volume of ascites (* in B). Findings are nonspecific but suggestive of early ischemia or infection. Image courtesy of RSNA

A complex multicompartmental cerebral hemorrhage on a single axial CT image displayed using the annotation tool in a single portal window. Hemorrhage labels (left column) relevant to the image display on the bottom of the image once selected. ASNR = American Society of Neuroradiology RSNA = Radiological Society of North America. Image courtesy of RSNA

According to the 10 authors from multiple institutions across the US who reviewed the most frequently cited studies on the subject: 'Test performance and management issues arise when inappropriate and potentially overreaching conclusions regarding the diagnostic performance of CT for COVID-19 pneumonia are based on low-quality studies with biased cohorts, confounding variables, and faulty design characteristics. Image courtesy of American Journal of Roentgenology (AJR)

U.S. Army Spc. Jonathon Hyde and Spc. Casymn Harrison from the 1434th Engineer Company, Grayling, Mich., Michigan National Guard, prepare patient rooms at TCF Regional Care Center in Detroit in advance of receiving COVID-19 patients, April 9, 2020. The TCF Center in Detroit has been converted into a 970-bed alternative care facility for COVID-19 patients by the Federal Emergency Management Agency, in partnership with the U.S. Army Corps of Engineers and Michigan National Guard. (Photo courtesy of U.S. Air National Guard photo by Master Sgt. Scott Thompson)

Maps of stiffness (storage modulus) in uniform-concentration sample (left) and sample with harder inclusion (right) (sample: polyacrylamide gel). It can be seen that harder inclusion is clearly visible in spite that its concentration is only slightly different from the surrounding matrix. Note that such a slight difference cannot be discerned by typical X-ray radiography for medical diagnostics. Image courtesy of Wataru Yashiro, the Institute of Multidisciplinary Research for Advanced Materials (IMRAM), Tohoku University

United Imaging has installed its first transportable CT Scanner at Maimonides Medical Center in New York City to help expand its capacity for imaging during the fight against coronavirus in the U.S. As the hospital scales its operations to meet the needs of an expected influx of coronavirus patients, doubling its capacity to 1,400 beds, United Imaging’s scanner will help expand its capacity for imaging studies to support diagnosis and treatment.